deep-research

To transform a vague product concept into a ship-ready specification, apply a six-phase deep research methodology covering concept extraction, landscape survey, constraint discovery, shape definition, risk assessment, and output crystallization to produce structured documentation.

Risk assessment during product specification generation is best handled through a phased analysis approach that evaluates project constraints and shapes feature definitions, resulting in a comprehensive research brief and a machine-readable feature request.

A phased analysis methodology for product documentation works by sequentially processing inputs through concept extraction, landscape survey, constraint discovery, shape definition, risk assessment, and crystallization to yield both human-readable briefs and machine-readable JSON feature requests.

No external dependencies or components are required to run deep research for feature requests. The process requires only standard documentation inputs to generate the defined research brief and feature request outputs.

Yes, you can output a machine-readable feature request alongside a human-readable research brief. The methodology crystallizes inputs into both formats, enabling seamless handoff from planning to implementation.

You should use a landscape survey in product specification planning during the early phases of research to map the existing environment and discover constraints before defining the feature shape and assessing risks.